Legal claims defining the scope of protection, as filed with the USPTO.
1. A method, comprising: extracting, by a computer system, a first plurality of information objects from a natural language text; extracting, from the natural language text, a second plurality of information objects; determining that a first textual annotation associated with a first information object of the first plurality of information objects is overlapping with a second textual annotation associated with a second information object of the second plurality of information objects; applying, to the first information object and the second information object, a conflict arbitration function represented by a machine learning classifier yielding a likelihood of the first information object and the second information object representing a same object.
2. The method of claim 1 , wherein extracting the first plurality of information objects is performed by a first information extraction technique and extracting the second plurality of information objects is performed by a second information extraction technique.
3. The method of claim 1 , further comprising: producing a final list of information objects extracted from the natural language text; and utilizing the final list of information objects for performing a natural language processing operation.
4. The method of claim 1 , further comprising: producing a final list of information objects extracted from the natural language text; and representing the final list of information objects by a Resource Definition Framework (RDF) graph.
5. The method of claim 1 , further comprising: evaluating a logical condition comprising a first attribute of the first information object and a second attribute of the second information object.
6. The method of claim 1 , further comprising: determining that the first information object has a number of attributes of a certain type exceeding a threshold number of attributes of the certain type.
7. The method of claim 1 , further comprising: appending, to a training data set, the natural language text accompanied by metadata comprising definitions and textual annotations of the first information object and the second information object; and training, utilizing the training data set, a machine learning classifier implementing the conflict arbitration function.
8. The method of claim 1 , further comprising: determining a first confidence level associated with the first information object.
9. A computer system, comprising: a memory; a processor, coupled to the memory, the processor configured to: extract a first plurality of information objects from a natural language text; extract, from the natural language text, a second plurality of information objects; determine that a first textual annotation associated with a first information object of the first plurality of information objects is overlapping with a second textual annotation associated with a second information object of the second plurality of information objects; and apply, to the first information object and the second information object, a conflict arbitration function represented by a machine learning classifier yielding a likelihood of the first information object and the second information object representing a same object.
10. The computer system of claim 9 , wherein extracting the first plurality of information objects is performed by a first information extraction technique and extracting the second plurality of information objects is performed by a second information extraction technique.
11. The computer system of claim 9 , wherein the processor is further configured to: produce a final list of information objects extracted from the natural language text; and utilize the final list of information objects for performing a natural language processing operation.
12. The computer system of claim 9 , wherein the processor is further configured to: produce a final list of information objects extracted from the natural language text; and represent the final list of information objects by a Resource Definition Framework (RDF) graph.
13. The computer system of claim 9 , wherein the processor is further configured to: evaluate a logical condition comprising a first attribute of the first information object and a second attribute of the second information object.
14. The computer system of claim 9 , wherein the processor is further configured to: append, to a training data set, the natural language text accompanied by metadata comprising definitions and textual annotations of the first information object and the second information object; and train, utilizing the training data set, a machine learning classifier implementing the conflict arbitration function.
15. The computer system of claim 9 , wherein the processor is further configured to: determine a first confidence level associated with the first information object.
16. A computer-readable non-transitory storage medium comprising executable instructions that, when executed by a computer system, cause the computer system to: extract a first plurality of information objects from a natural language text; extract, from the natural language text, a second plurality of information objects; determine that a first textual annotation associated with a first information object of the first plurality of information objects is overlapping with a second textual annotation associated with a second information object of the second plurality of information objects; and apply, to the first information object and the second information object, a conflict arbitration function represented by a machine learning classifier yielding a likelihood of the first information object and the second information object representing a same object.
17. The computer-readable non-transitory storage medium of claim 16 , wherein extracting the first plurality of information objects is performed by a first information extraction technique and extracting the second plurality of information objects is performed by a second information extraction technique.
18. The computer-readable non-transitory storage medium of claim 16 , further comprising executable instructions that, when executed by the computer system, cause the computer system to: produce a final list of information objects extracted from the natural language text; and utilize the final list of information objects for performing a natural language processing operation.
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June 23, 2020
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